Author:
Medhi kishore,Jamil Md.,Hussain Iftekhar
Abstract
COVID-19 infection has created a panic across the globe in recent times. Early detection of COVID-19 infection can save many lives in the pre-vailing situation. This virus affects the respiratory system of a person and creates white patchy shadows in the lungs. Deep learning is one of the most effective Artificial Intelligence techniques to analyse chest X-ray images for efficient and reliable COVID-19 screening. In this paper, we have proposed a Deep Convolutional Neural Network method for fast and dependable identification of COVID-19 infection cases from the patient chest X-ray images. To validate the performance of the proposed system, chest X-ray images of more than 150 confirmed COVID-19 patients from the Kaggle data repository are used in the experimentation. The results show that the proposed system identifies the cases with an accuracy of 93%.
Publisher
Cold Spring Harbor Laboratory
Cited by
24 articles.
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